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Lower instantaneous entropy of heartbeat dynamics characterizes cognitive impairment in Parkinson's disease

Barbieri, R and Valenza, G and Citi, L and Guerrisi, M and Orsolini, S and Tessa, C and Diciotti, S and Toschi, N (2014) Lower instantaneous entropy of heartbeat dynamics characterizes cognitive impairment in Parkinson's disease. In: UNSPECIFIED, ? - ?.

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Abstract

It has been estimated that the incidence of cognitive deficits in Parkinson's disease (PD), ranging from Mild Cognitive Impairment (MCI) to frank dementia, is six-fold compared to that in the general population. Also, P D involves postganglionic sympathetic failure and, in 25% of patients, autonomic failure. PD patients commonly present a range of ANS-dysfunction related symptoms. Since cognitive impairment has been previously linked with cardiovascular dysautonomia in PD, in this paper we investigate whether a link exists between autonomic complexity and MCI in PD. To this end, we employ our recently developed instantaneous measures of complexity, which have been explicitly designed for stochastic time series with binary events that occur in continuous time: the inhomogeneous point-process approximate and sample entropy (ipApEn and ipSampEn, respectively). Experimental results obtained by comparing 8 cognitively preserved (PD-NC) to 8 PD-MCI subjects during resting state demonstrate that grand average values of ipSampEn are able to differentiate the two groups. This suggests that a significant loss of time-varying cardiovascular complexity is associated with MCI in PD. Importantly, no other heart rate variability (HR V) measures differed significantly between groups, possibly pointing toward subtle autonomic changes (not detectable through conventional HRV analysis) which accompany the initial stage of cognitive impairment in PD.

Item Type: Conference or Workshop Item (Paper)
Additional Information: Published proceedings: Computing in Cardiology
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Science and Health > Computer Science and Electronic Engineering, School of
Depositing User: Luca Citi
Date Deposited: 08 Jan 2016 12:35
Last Modified: 17 Aug 2017 17:29
URI: http://repository.essex.ac.uk/id/eprint/15762

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